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To Decrease the Rate of Cyber Anomalies Using Intrusion Det..:

, In: 2024 2nd International Conference on Disruptive Technologies (ICDT),

Tomar, Anshika ; Umrao, Sandhya ; Kumar, Dileep - p. 1439-1442 , 2024

Link: https://doi.org/10.1109/ICDT61202.2024.10489366

RT 
T1 <cTitle>2024 2nd International Conference on Disruptive Technologies (ICDT)</cTitle>: T1 <Title>To Decrease the Rate of Cyber Anomalies Using Intrusion Detection System with Feature Selection Approach</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10489366&Exemplar=1&LAN=DE
				
A1 Tomar, Anshika
A1 Umrao, Sandhya
A1 Kumar, Dileep
YR 2024
K1 Surveys
K1 Support vector machines
K1 Statistical analysis
K1 Neural networks
K1 Intrusion detection
K1 Machine learning
K1 Feature extraction
K1 Intrusion Detection System
K1 Feature Selection
K1 Cyber Anomalies
K1 Network Security
K1 Threat Detection
K1 Machine Learning
K1 Anomaly Detection
K1 Data Mining
K1 Classification Algorithms
K1 Network Traffic Analysis
K1 Security Measures
K1 Information Security
K1 Malware Detection
K1 Pattern Recognition
K1 Attack Detection Risk Management
K1 Performance Evaluation
SP 1439
OP 1442
LK http://dx.doi.org/https://doi.org/10.1109/ICDT61202.2024.10489366
DO https://doi.org/10.1109/ICDT61202.2024.10489366
SF ELIB - SuUB Bremen

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